{"id":"W4415622466","doi":"10.1145/3772716","title":"Are Word Suggestions Beneficial? The Effect of Typing Efficiency and Suggestion Accuracy","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Computer-Human Interaction","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Typing; Word (group theory); Feature (linguistics); Automation; Character (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009899998,0.001062567,0.001196006,0.001098994,0.0004621802,0.002655027,0.001118048,0.00177206,0.003945665],"category_scores_gemma":[0.2093809,0.0007615896,0.0009139634,0.000939135,0.001214595,0.004144389,0.001210349,0.001466205,0.0006427756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003404696,"about_ca_system_score_gemma":0.0006682465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009304876,"about_ca_topic_score_gemma":0.001216531,"domain_scores_codex":[0.9855688,0.007218215,0.002151011,0.001590301,0.002771056,0.0007005174],"domain_scores_gemma":[0.508392,0.434419,0.03250575,0.01460924,0.007340187,0.002733758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.02473343,0.003360511,0.7296025,0.0048406,0.002803619,0.0006458712,0.005826541,0.006103849,0.05665269,0.0008847107,0.001164387,0.1633812],"study_design_scores_gemma":[0.0003798161,0.005658065,0.9766346,0.0003162938,0.001684972,0.0003727427,0.001325302,0.003324595,0.007908469,0.001224481,0.001082911,0.00008789914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930559,0.001071533,0.003363054,0.00021351,0.00004729286,0.00008781924,0.0001441867,0.0001092569,0.0019075],"genre_scores_gemma":[0.9947962,0.000350818,0.003782562,0.0001160219,0.00003955697,0.00009348024,0.0001307458,0.000087334,0.0006033122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009899998,"threshold_uncertainty_score":0.05235684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340600074081663,"score_gpt":0.2979896261012589,"score_spread":0.2845836253604422,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}